An Exploration of the Determinants of Bribery in Benin’s ...in Sierra Leone. They record the...

AGRODEP Working Paper 0028

June 2016

An Exploration of the Determinants of Bribery in Benin’s

Transborder Trade

Sami Bensassi

Joachim Jarreau

Cristina Mitaritonna

AGRODEP Working Papers contain preliminary material and research results. They have been peer

reviewed but have not been subject to a formal external peer review via IFPRI’s Publications Review

Committee. They are circulated in order to stimulate discussion and critical comments; any opinions

expressed are those of the author(s) and do not necessarily reflect the opinions of AGRODEP.

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About the Authors

Sami Bensassi is a lecturer in economics at University of Birmingham, UK.

Joachim Jarreau is an assistant professor of economics at University of Paris Dauphine, Paris, France.

Cristina Mitaritonna is a senior economist at Centre d'études prospectives et d'informations internationales

(CEPII), Paris, France.

Acknowledgements

This project has benefited from a grant from AGRODEP under the Gaps in Research Grant program. We

gratefully acknowledge the anonymous referee for his constructive comments.

This research was undertaken as part of, and partially funded by, the CGIAR Research Program on Policies,

Institutions, and Markets (PIM), which is led by IFPRI and funded by the CGIAR Fund Donors. This paper

has gone through AGRODEP’s peer-review procedure. The opinions expressed here belong to the authors,

and do not necessarily reflect those of AGRODEP, IFPRI, PIM or CGIAR.

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Table of Contents

1. Introduction ........................................................................................................................... 6

2. Benin: An Entrepot Economy .............................................................................................. 7

3. Informal and Formal Taxation of International Trade in Benin ...................................... 7

4. A First Exploration of the Relationship between Informal Taxation and Total Value of

the Goods Exchanged ................................................................................................................. 12

4.1 Methodology ....................................................................................................................12

4.2 Results .............................................................................................................................14

Conclusion ................................................................................................................................... 19

References .................................................................................................................................... 20

AGRODEP Working Paper Series ............................................................................................ 21

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Abstract

Few studies give a systematic account of the bribes paid by smugglers to different groups of state actors.

Nonetheless, smuggling is a very pervasive phenomenon in West Africa which could impact state revenues,

trade routes, consumption patterns, and wealth in the region. This study is based on a survey conducted by

the Benin Institute of Statistics that attempts to record all illegal transactions at Benin’s borders for the span

of one week. Our aim is to understand whether the quantity and/or the quality of the goods exchanged play

a role in the determination of informal taxes. Better understanding the mechanisms driving the

determination of the informal taxes will help authorities and local actors reduce informal trade.

Résumé

Peu d’études proposent une revue systématique des pots-de-vin payés par les contrebandiers aux acteurs

étatiques. Pourtant, la contrebande est un phénomène très répandu en Afrique de l’Ouest qui impacte les

revenues des Etats, les routes commerciales, les habitudes de consommation et la distribution des richesses

dans la région. Cette étude est basée sur une enquête menée par l’institut national statistique du Benin qui

avait pour objectif d’enregistrer toutes les transactions illégales aux frontières du Benin durant une semaine.

Notre objectif est de comprendre si les quantités ou la qualité des biens échangés jouent un rôle dans la

détermination des taxes informelles. Une meilleure compréhension des mécanismes conduisant à la

détermination de celles-ci pourrait permettre aux autorités et aux acteurs locaux de réduire le commerce

informel.

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1. Introduction

Few studies provide a systematic account of the bribes paid to different state actors in order to smuggle

goods across borders. Titeca and Celestin (2012) research the informal and formal payments made in

several border localities in the Democratic Republic of Congo, Burundi, Rwanda, and Uganda. They note

that these payments have are highly variable, with the informal tax being superior to the formal tax paid in

some instances. Jibao, Prichard, and van den Boogard (2015) analyze data gathered at two border passages

in Sierra Leone. They record the nature of the payments, goodwill payments, acceleration fees, and

payments in nature, as well as the amount of the bribes paid by traders to government officials. Their

findings underline the role of social norms, networks, and power imbalances in determining the amounts

and types of payments made by informal traders.

Obtaining and analyzing information regarding the informal payments made to government officials is

important for several reasons:

Informal taxation is a direct cost to trade; its extent (number of different products for which an

informal payment may be demanded) and its depth (the value of the tax) can have consequences

on the nature and the quantity of goods exchanged.

Different levels of informal taxation between countries may play a role in the trade routes

selected by merchants.

The revenue generated by informal taxation creates distorted incentives for government

officials.

Information taxation may have a strong impact on the formal tax revenue generated by the

state, as one of the main motivations for informal tax payments is to avoid the payment of

formal taxes. However, little is known about how much the formal tax rate serves as a

benchmark for informal tax negotiations and payments.

In this paper, we focus on the role of informal taxation as a cost to trade in the case of Benin using the

ECENE1 survey. In Section 2, we give a brief overview of the literature directly concerned with Benin’s

informal trade. In Section 3, we present descriptive statistics showing the average amount of informal and

formal taxes paid in different trading situations (import, export, re-export, transit, and for the goods most

intensively exchanged at Benin’s borders); in Section 4, we explore the relationship between informal

taxation and the total value of the goods exchanged. Section 5 concludes.

1 Enquête sur le commerce extérieur non enregistré

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2. Benin: An Entrepot Economy

Golub (2012) follows Igue and Soule (1992) in describing Benin as an Entrepot economy, writing: "Benin,

Togo and Gambia serve as conduits for both legal transit to landlocked countries in West Africa (Niger,

Mali and Burkina Faso) and illegal trade to more protectionist countries (Senegal and Nigeria)". His paper

suggests the existence of various illegal trade channels in Benin, such as the use of third countries such as

Niger to get goods into Nigeria. The trade of second-hand cars from Benin to Nigeria and the smuggling of

Nigerian oil into Benin and Togo via Benin seem to be of particular importance.

Both of these products have been the object of several papers and reports; Golub (2012), INSAE (2008),

and Bako-Arifari (2001) focus on the car trade, while Agbachi (2012) and LARES (2005) focus on the

smuggling of gasoline. The INSAE (2008) report gives a detailed account of the steps required to export a

second-hand car through the port of Cotonou; the customs procedures (apposition of special identification

plates for transit vehicles), the payment made, and the economic actors involved (both informal and re-

salers) are all clearly identified. According to the authors of the report, the multiplication and de-

centralization of trade procedures was according the main reason for the existence of informal payments in

2008.

Golub (2012) suggests that taxes and fees on transit produce sizeable revenues for Benin’s customs2. The

LARES (2005) report describes the oil smuggling supply chain from Nigeria to Benin. Gasoline is bought

legally in Nigeria and stocked close to the Beninese border. From there, the informal cycle of gasoline

commercialization starts with forwarders, wholesalers, transporters, and paddlers from Benin. Agbachi

(2012) details two main categories of wholesalers. One group has large capital assets and organizes

smuggling and distribution activities in Cotonou through various agents. The other group, with less

financial assets, has to go to Nigeria to organize passage of the goods. Wholesalers, both big and small,

tend to avoid crossing borders with their goods themselves and instead delegate this activity to inhabitants

of the border areas. While the studies mentioned here describe the mechanisms of this traffic, however,

none provide an insight into how much illegal payment is needed to lubricate the engines of trade.

3. Informal and Formal Taxation of International Trade in Benin

The ECENE survey has been implemented by the National Institute of Statistics of Benin. Its objective is

to quantify informal trade at Benin’s borders. The survey, conducted in September 2011, covers 171 border

crossing passages identified as actively used by smugglers. Questionnaires addressed to informal traders

gathered information regarding the nature, quantity, and value of smuggled goods. The ECENE survey does

2 The World Trade Organisation, Trade Policy Review for Benin (Organization, 2010) notes that the custom escort, the mandatory

escort for transiting vehicles from the port of Cotonou to Benin’s borders, represented 4 percent of the state’s fiscal revenue in

2008.

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not contain information regarding the nature of the bribes; however, it provides the amount of both informal

tax and formal tax paid by the traders for each transaction observed during the period of the survey. More

specifically, the two questions regarding taxation encompass the following payments:

How much the traders have paid informally to state agents to cross the borders with their

merchandises. This includes all the payments made during the transport of the goods for which

the traders received no official receipts. For example, bribes paid at road blocks manned by the

army, the police, or the customs agency or to escape the control of these agencies, and

How much traders have paid formally; that is to say, payments for which they have received a

receipt during the export or import process. For example, taxes collected by local authorities.

The survey records 8,883 border crossings and identifies 10,415 flows of goods (INSAE, 2011). Of those,

1,165 border crossings are multi-products; that is to say, for example, a truck transporting yams, wheat

flour, and worn clothing. Two-thirds of these border crossings (or 770) involve only two goods, while only

28 crossings involve more than six goods. These multi-products crossing encompass 2,945 flow of goods.

The average total value of the cargo per crossing crossings is USD 4,507, which is far more than the USD

1,841 average value of the cargo per crossing for the 6,820 single-product trade flows recorded. However,

the average value per good transported in multi-product cargo, USD 428, is less important. The structure

of the ECENE database attributes formal and informal payment to border passage and not to a specific

good. In the following, multi-product trade flows will be included when we present descriptive statistics or

regressions over aggregate figures corresponding to the total value of shipments. When we investigate

particular products and the taxes (informal or formal) paid for their passage, the observations originating

from multi-product cargo are left aside, as there is no way to attribute the informal and/or formal tax

payment recorded to a particular good.

Column 2 of Table 1 shows the average level of informal and formal taxation for import, export, re-export,

and transit trade for multi- and single-product flows. Goods considered under the re-export or transit regime

benefit from formal tax exemptions at the entrance to Benin3. The maximum level of average informal and

formal tax recorded is for transit trade (respectively, USD 24.3 and USD 123.22). In column 4 of the same

table, the average of the ratio of informal (formal) taxation over the total value of the good transported is

displayed. These rates are low no higher than 2 percent for informal taxes and no higher than 5 percent for

formal taxes.

3 However, special taxes and duties might substantially increase the overall payment. The used vehicle trade constitutes a good

example. Before being able to re-export a second-hand vehicle, the owner of the vehicle should pay a statistical tax (5 percent of

the value of the vehicle), a custom stamp duty, a special standing advance (CFA50000) (these three taxes can be refunded in case

of export to a landlocked neighboring country), a custom escort (CFA75000), a computer fee (CFA2000), and between 2004 and

2009, an eco-tax depending on the size of the vehicle (World Trade Organization, 2010). It must be noted that many of these special

taxes and duties are dependent on the valuation made of the goods by customs agents

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We believe it is important if a trader has reported paying either no formal or no informal tax, or both,

because this may point to economic agents who have chosen to pay a bribe in order to avoid formal taxation

(positive informal tax and zero formal tax), who have chosen to pay the formal tax and not the informal tax

(zero informal and positive formal), or who are connected enough to avoid payment of both the formal and

the informal tax (zero formal and informal). In column 6, of Table 2, we display the number of null

observations, while column 7 shows the ratio of null observations over the total number of observations.

Transit shows a remarkable rate of payment of the informal tax (only 8 percent of the respondents declare

having paid zero against a maximum of 30 percent null payment for export) and formal tax (only 26 percent

of the respondents declare having paid zero against a maximum of 64 percent for re-export). It should be

noted that the number of respondents systematically drops when asked about the amount of formal tax paid.

This may be due to the fact that respondents prefer to avoid answering when they have paid no formal tax

at all. For transit, only 33 percent of the individuals who report having made no informal payment also

report having paid nothing formally; this rate is very different for the other trade channels, which range

from a minimum of 71 percent (import) to a maximum of 86 percent (re-export).

Table 1: Descriptive Statistics

Mean SD Average

Tax Ratio

Number of

Observations

Number of

Null

Payments

Ratio of Null

Payments

All transactions Informal

Tax 13.85 84.67 2% 7920 1646 20%

Formal Tax 17.09 189.61 1% 5662 3035 53%

Import Informal Tax 16.35 101.55 2% 5000 979 20%

Formal Tax 14.93 222.39 1% 3564 1860 52%

Export Informal Tax 6.66 28.65 2% 1534 450 30%

Formal Tax 4.21 31.31 1% 1212 713 59%

Re-Export Informal Tax 9.53 55.49 1% 1017 175 17%

Formal Tax 6.73 65.24 0.06% 596 379 64%

Transit Informal Tax 24.35 46.08 1% 311 26 8%

Formal Tax 123.22 284.23 5% 235 61 26%

Source: ECENE survey 2011

Table 2 presents products for which we have decided to provide a more detailed analysis in terms of

informal and formal taxation in Table 3. The data in the Table 2 come from single-product flows, as we

cannot associate the level of taxation to a particular product with multi-product flows. The products in the

table are the most intensively exchanged (at least over 100 observations per trade flow) over the period of

the survey. We end up with 11 flows for 10 categories of goods (at the HS4 classification level). Table 2

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indicates the type of flow (export, re-export, transit, import), the country of destination for export, re-export,

and transit or origin for import, and an indication of the tariff regime in place for these products. Nigeria is

the main destination of Benin’s exports, re-export, and transit trade, apart for the re-export of gasoline. The

products imported to Benin come from Nigeria and Togo. Foods (fresh tomatoes, rice, maize, manioc and

yam) and processed foods (palm oil, chicken meat, wheat flour and manioc flour) are the most frequently

traded items over the period of observation. Second-hand cars are the only manufacturing good that we

capture. Trade in gasoline is frequent in terms of import to Benin and re-export to Togo.

Table 3 completes the information provided in Table 2 with data on the average informal and formal tax

paid for these products, the average total value per transaction, and the unit value of the products (with the

exception of second-hand cars, for which the total value is also the unit value of the car). The importance

of the

Table 2: Products studied: Number and Direction of the flows

HS Code Number of

Observation

Flow Product Destination/

Origin

Tariffs

0702 207 Exportation Fresh Tomatoes Nigeria 20%

0714 158 Exportation Manioc and Yam Nigeria and Togo Nigeria: 20% +

15%, Togo: 0%

1511 227 Exportation and

Re-exportation

Palm Oil Nigeria Ban

1006 245 Re-exportation Rice Nigeria 10% levy

[20%;60%]

0207 122 Re-exportation Chicken meat Nigeria Ban

2710 288 Re-exportation Gasoline Togo Illegal

8703 137 Transit Second handed

Cars

Nigeria 5% + [20%;35%]*

1005 186 Import Maize Togo 0%

1101 148 Import Wheat Flour Nigeria 20%

1106 118 Import Manioc Flour Togo 0%

2710 1851 Import Gasoline Nigeria Illegal * A ban exist for the second-hand cars older than 8 years

car, transit, and gasoline import trade is confirmed with a high average total trade value (USD 10,843 for

second-hand cars and USD 2,800 for gasoline imports). The average value of rice re-export is close to these

levels, but still lower than the average value of gasoline import (USD 2,173); however, formal and informal

taxes are far more important for gasoline imports.

The existence of a formal tax for gasoline imports is per se an interesting element. Imports of oil by non-

licensed companies in Benin is forbidden, and no taxes should be collected on illegal imports; nonetheless,

according to Agbachi (2012), some customs agents applied a tariff of 10 percent on the value of the gasoline

imported and/or informally taxed traders to abandon pursuits against smugglers. Interestingly, the import

of maize and manioc flour from Togo to Benin show a positive formal tax (respectively, USD 6.43 and

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USD 0.4) even though the two countries belong to the same regional trade agreement and no tariffs are

officially applied on these goods. As the definition of formal tax includes taxes by local authorities, these

observations might point to taxation on imports from these local institutions regardless of the origin of the

products or to a formal tax constructed by them, as in the case of gasoline imports.

Column 4 of Table 3 displays the average informal (formal) tax ratio. The informal tax ratio, with the

exception of the second-hand car trade, is systematically superior to the formal tax ratio. The relatively high

formal tax ratio for second-hand car transit (10.30 percent) and the fact that this transit largely dominates

the informal tax ratio (0.30 percent) might suggest that the central government has better control of the tax

revenue generated through this trade. Even though it has been noticed (INSAE, 2008) that the multiplication

of agents intervening in the car trade is a source of informal payment, the concentration of this trade on a

well-identified single location – i.e., inside the port of Cotonou – might make the avoidance of formal tax

payment difficult.

Table 3: Products studied: Formal and Informal Tax

Mean SD Average

Tax Ratio

Number of

Observations

Number of

Null

Payment

Ratio of

Null

Payment

Maize (1005) Import

Informal Tax 2.5 6.97 3.40% 186 27 15%

Formal Tax 6.43 62.89 1.80% 167 40 24%

Total value (Transaction) 150.49 430.63 186

Unit Value 0.33 0.13 186

Flour Wheat (1101)

Import

Informal Tax 10.81 29.94 1.60% 148 8 5%

Formal Tax 13.05 76.63 0.70% 92 76 83%


Unit Value 0.813 0.173 148

Flour Manioc (1106)

Import

Informal Tax 1.58 3.2 5.20% 118 20 17%

Formal Tax 0.4 0.79 1.00% 87 45 52%


Unit Value 0.36 0.83 118

Mineral Fuel (2710)

Import

Informal Tax 31.68 157.03 1.60% 1851 110 6%

Formal Tax 35.16 390.54 1.00% 1078 436 40%


Unit Value 0.52 0.67 1851

Tomatoes (0702) Export

Informal Tax 5.48 21.15 2.10% 203 68 33%

Formal Tax 2.72 10.71 0.40% 141 110 78%


Unit Value 0.36 0.16 203

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Manioc (0714) Export

Informal Tax 4.91 9.04 3.00% 158 47 30%

Formal Tax 4.24 8.6 1.60% 134 67 50%


Unit Value 0.27 0.35 158

Palm oil (1511) Export

and Re-export

Informal Tax 3.46 9.97 0.60% 227 34 15%

Formal Tax 3.94 23.43 0.20% 158 108 68%


Unit Value 1.36 0.42 227

Rice (1006) Re-export

Informal Tax 5.37 23.2 0.40% 245 60 24%

Formal Tax 4.63 22.44 0.10% 147 99 67%


Unit Value 0.64 0.27 245

Mineral Fuel (2710) Re-

export

Informal Tax 14.54 69.52 2.40% 288 82 28%

Formal Tax 2.61 6.37 0.70% 207 117 57%


Unit Value 0.76 0.25 288

Car (8703) Transit

Informal Tax 16.71 30.67 0.30% 137 4 3%

Formal Tax 259.74 384.1 10.60% 99 24 24%

Total value (Transaction) 10843.69 23448.19 137 Source: ECENE survey 2011

4. A First Exploration of the Relationship between Informal Taxation and Total Value of

the Goods Exchanged

4.1 Methodology

Jean and Mitaritonna (2010) propose a model that determines the amount of bribery paid to government

agents. In this model, traders can choose whether or not to bribe the officials, and officials can choose

whether or not to take those bribes. Traders can also try to hide the real value of shipments, and bribed

officials incur the risk of being caught. We believe this model is well-suited to describing the reward of

smuggling for officials and firms in the developed world, where functioning institutions can enforce

punishment mechanism. However, anecdotal evidence suggests that it might be ill-suited to explaining

bribery in the developing world.

Jibao, Prichard, and van den Boogard (2015) say about Sierra Leone that "both border officials and

chatterman are able to exploit the information and power asymmetries...which effectively allow traders

little option to opt out of the informal system." They also report a customs official saying at the border

crossing, "The president may control the State House, but we determine what happens here and what we

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obtain from the post". The situation in Sierra Leone may be an extreme case, but we tend to believe that

even in Benin, the central government’s control may not be strong enough to make the threat of punishment

credible enough to play a role in traders’ and officials’ decisions regarding bribery.

Evidence from descriptive statistics also shows that informal payments are widespread. In addition, Walther

(2015) shows that in the West African context, the trade network and the social capital of the traders

embedded in that network can play an important role through the personal connections that individuals have

with state government officials at border crossings or in the central government. In a situation in which

central government control over the agencies acting at the borders is low and bribery widespread, the

amount of bribes paid to government officials might depend on a function of the number of interactions

between the government officials and traders during the export or import process, the total value of the

smuggled goods identified by the government agent during each interaction, and the distance in terms of

social capital between the trader and the government official negotiating formal and informal taxes during

each interaction. More formally:

(1)

where the total informal amount paid bribe for a particular good i and a particular shipment j (import or

export) is the sum of the number of interactions k between traders a and government officials b over this

shipment. During each interaction, a bribe is negotiated. The value of the bribe depends on the distance in

terms of social capital τ between individuals a and b, the effort made by the traders to conceal his shipment

δ, and the total value v of the good transported i during this transaction j.

While it is clear that the number of interactions and the total value of the goods transported should have a

positive impact on the total bribes paid to import or export that good, the effect of distance in terms of social

capital is more ambiguous and might be different according to the type of payment made. For example,

family links or friendships between traders/peddlers and customs agents at the border crossing might

increase the probability that goodwill payments are made but might limit other types of payments. Similarly,

agents of large traders/wholesalers might have the power to eliminate informal and formal payments at

border crossings, but at the same time, they might hesitate to use this capital and prefer to maintain cordial

relationships with local government officials through the payment of informal taxes. The more knowledge

a trader develops in terms of how to conceal his shipment (by choosing routes that avoid government

officers or by concealing the most valuable part of his cargo, for example), the less informal (and formal)

tax they should pay. The ECENE survey provides a good record of the informal payments made and the

total value of the goods exchanged; however, no specific module in the ECENE survey directly questions

the respondents about their social capital or/and trade networks. We try to proxy these variables through

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the nationality of the agent organizing the border passage and the function in the supply chain (wholesalers,

intermediary, retailers, etc.) of the clients or suppliers of the firm organizing the border passage. We also

control for the size of the firm, as bigger firms might be more connected to local or national governments

than their smaller counterparts.

We observe all the outcomes at their true value. However, our dataset contains a significant number of 0,

making our sample distribution censored to the left. In case of a corner solution response, as we do have

with our dependent variable, the coefficient obtained from classic linear regression will be inconsistent.

The Tobit model is appropriate to tackle the problems posed by corner solution response (Wooldridge,

2008). Our econometric specification is based on the following equation:

bribeij = β1uvij +β2Qij +αXij +µ (2)

where uvij is the unit value of the good transported in CFA franc (we calculate a weighted average unit value

for multi-products trade flows), Qij is the quantity of goods transported in kg (we use the total quantity of

the shipment for multi-product trade flows), Xij is a vector of control variables accounting for the nationality

of the agent (Beninese or not), the function in the supply chain of the clients or suppliers of the agent

organizing the border passage (wholesalers or not), the size of the firm (approximated through its number

of workers: family members, employees, and casual workers), the different type of goods transported in

one passage (ranging from 1 when only type of products is transported to 11), the type of flow of goods

(import, export, re-export, or transit), and whether the trade is originated to or bound to Nigeria. µ is an

error term.

4.2 Results

Table 4 shows our results for informal payments. We produce the same exercise for formal payment in

Table 5. Both tables are divided into two parts; columns 2,3, and 4 show the results for the amount of

informal tax paid (the formal amount paid in Table 5), while columns 5, 6, and 7 show the results for the

informal tax ratio (the formal tax ratio in Table 5). Columns 2 and 5 in Table 4 and Table 5 present our

results for all the trade flows observed, while columns 3 and 6 show only the multi-product trade flows

and columns 4 and 7 show only the single-product trade flows.

We find a significant and positive relationship between the quantity of goods transported (weight in kg),

their unit value (weighted unit value), and the informal tax paid. This relationship also holds for the formal

tax paid. Not surprisingly, the amount of (in)formal tax paid increases with the value and the quantity of

the goods transported. However, this relationship is reversed for the informal tax ratio, for which a negative

and significant relationship links the quantity of goods transported, their unit value, and the informal tax

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ratio. The more the smugglers transport in one load in terms of value and quantity, the less informal tax

they will pay relative to the total value of the goods transported.

The relationship between quantity transported and the formal tax ratio is significant and positive (albeit it

is not significant for the multi-product flows) and negative and significant between the unit value and the

formal tax ratio (the same words of caution apply to the significance of the coefficient for the multi-product

flows).

The variables we used to control the role of networks (firms domiciled in Benin) and the position in the

smuggling value chain (connection to a wholesaler) show interesting linkages with the dependent variables,

particularly when we contrast informal payments and the informal tax ratio on one side and formal payments

and the formal tax ratio on the other. Smugglers who declared their activity domiciled in Benin seem to

consistently pay more informal tax in terms of amount paid or ratio than their counterparts not domiciled

in Benin. The same seems to be true for the smugglers connected to wholesalers.

Turning to formal taxation, the relationship between formal tax levels or the formal tax ratio and firms’

domicile in Benin is negative and significant. The relationship with formal tax levels or the formal tax ratio

and connection with wholesalers is also negative and significant for single-product trade flows. These

results suggest that well-connected firms may be more efficient at avoiding formal tax payments by paying

informal ones.

The number of different products is significantly and negatively linked to both the informal and the formal

tax ratio when we consider all the products, pointing to the possibility that multi-product cargo might be

used to deter the attention of the authorities from the most valuable goods.

We also control for the direction of trade flows: import, export, re-export, and transit. In comparison to

imports, exports and re-exports generally show a significant and negatively relationship with the informal

level of tax, the informal tax ratio, the formal tax level, and formal tax ratio. Transit does not show

significant differences from imports in terms of its relationship with the level of informal tax and the

informal tax ratio. However, transit does show a significant and positive relationship with the formal level

of tax and the formal tax ratio in comparison to import flows. The results, at least in regards to the

relationship of exports and re-exports with formal tax levels and the formal tax ratio, are as expected,

considering that the tariff level for imports in Benin is higher on average that tariff level for goods exported

or re-exported from Benin. The fact that these relationships hold for informal taxation tends to confirm that

the level of informal taxation is negotiated in relation with the existing level of formal taxation. Transit

flows confirm a specificity already alluded to in the descriptive statistics. The average level of tariffs and

duty for transit (6 percent) are less than the average level of tariffs for import (7.8 percent); however we

16

have observed a higher level of tax collection for these flows, which may explain the positive relationship

between the transit control variable and the formal level of tax and formal tax ratio.

Finally, we control whether Nigeria is the country at either end of the trade flows. Most of the imports

observed in the ECENE survey come from Nigeria, and most of the exports, re-exports, and transit are

bound to Nigeria. The difference in price between Benin and Nigeria for the same goods, which is due to

several factors, helps to explain the importance of smuggling between the two countries. The Nigeria

dummy we introduce allows us to check whether demand factors on the Nigerian side for products coming

from Benin or on the Beninese side for Nigerian goods coming to Benin are associated with higher informal

and formal tax payments. We find a negative and significant relationship between trade with Nigeria and

the amount of formal tax paid or the ratio of formal tax and a positive and significant relationship between

trade with Nigeria and the amount of informal tax paid or the ratio of informal tax. In this instance again,

smugglers dealing with Nigerian trade seem to prefer avoiding formal payments by paying informal ones.

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Table 4: Results for informal tax value per trade flow in CFA and informal tax ratio

Tobit Model

Dependent Variable Dependent Variable

Informal Tax Value in CFA Informal Tax Ratio

Weight in kg (log) 0.959*** 0.903*** 0.977*** -0.001*** -0.002* -0.001**

(0.02) (0.08) (0.02) (0.00) (0.00) (0.00)

Weighted Unit value (log) 0.659*** 0.938*** 0.622*** -0.004*** -0.002 -0.004***

(0.04) (0.12) (0.04) (0.00) (0.00) (0.00)

Wholesaler links(d) 0.546*** 0.568* 0.525*** 0.003*** 0.005* 0.003**

(0.07) (0.26) (0.08) (0.00) (0.00) (0.00)

Firm domiciled in Benin (d) 0.368*** 0.753** 0.299** 0.002 0.005** 0.001

(0.09) (0.26) (0.10) (0.00) (0.00) (0.00)

Number of workers 0.008 0.026 0.007 0.000*** 0.000 0.000**

(0.01) (0.03) (0.01) (0.00) (0.00) (0.00)

Number of different products 0.120 0.110 -0.002*** 0.000

(0.06) (0.10) (0.00) (0.00)

Export (d) -0.873*** -0.196 -0.949*** -0.005*** -0.000 -0.005***

(0.10) (0.34) (0.10) (0.00) (0.00) (0.00)

Re-export (d) -0.550*** -0.698 -0.552*** -0.002 -0.006* -0.002

(0.11) (0.40) (0.12) (0.00) (0.00) (0.00)

Transit (d) -0.213 0.473 -0.315 0.001 -0.000 0.001

(0.18) (0.47) (0.19) (0.00) (0.00) (0.00)

Trade with Nigeria (d) 0.541*** 1.029*** 0.467*** 0.003** 0.009** 0.002

(0.09) (0.28) (0.10) (0.00) (0.00) (0.00)

r2p 0.071 0.044 0.077 -0.013 -0.024 -0.013

N 7920 1099 6821 7920 1099 6821

Nlc 1646 290 1356 1646 290 1356 (d) for discrete change of dummy variable from 0 to 1

* p<0.05, ** p<0.01, *** p<0.001

18

Table 5: Results for formal tax value per trade flow in CFA and formal tax ratio

Tobit Model

Dependent Variable Dependent Variable

Formal Tax Value in CFA Formal Tax Ratio

Weight in kg (log) 0.849*** 0.535*** 0.908*** 0.003*** 0.001 0.004***

(0.03) (0.09) (0.03) (0.00) (0.00) (0.00)

Weighted Unit value (log) 0.239*** 0.268* 0.222*** -0.002* -0.000 -0.002*

(0.05) (0.13) (0.05) (0.00) (0.00) (0.00)

Wholesaler links (d) -0.115 0.615 -0.256* -0.003* 0.001 -0.004**

(0.12) (0.32) (0.13) (0.00) (0.00) (0.00)

Firm domiciled in Benin

(d)

-0.372** -0.224 -0.411** -0.004** -0.004* -0.004*

(0.13) (0.29) (0.14) (0.00) (0.00) (0.00)

Number of workers 0.005 0.064** -0.003 0.000 0.000* 0.000

(0.13) (0.29) (0.14) (0.00) (0.00) (0.00)

Number of different

products

-0.125 0.037 -0.003*** -0.000

(0.08) (0.12) (0.00) (0.00)

Export (d) -0.338** 0.777* -0.471*** -0.002 0.001 -0.003

(0.12) (0.37) (0.13) (0.00) (0.00) (0.00)

Re-export (d) -1.120*** -0.744 -1.184*** -0.008*** -0.002 -0.009***

(0.14) (0.45) (0.15) (0.00) (0.00) (0.00)

Transit (d) 1.612*** 4.997*** 1.220*** 0.030*** 0.050** 0.028***

(0.32) (1.04) (0.32) (0.01) (0.02) (0.01)

Trade with Nigeria (d) -1.173*** -0.741* -1.325*** -0.007*** -0.002 -0.009***

(0.12) (0.30) (0.14) (0.00) (0.00) (0.00)

r2p 0.046 0.027 0.052 -0.290 -0.122 -0.390

N 5662 918 4744 5662 918 4744

Nlc 3037 516 2521 3035 516 2519

(d) for discrete change of dummy variable from 0 to 1

* p<0.05, ** p<0.01, *** p<0.001

19

Conclusion

Our descriptive statistic show the prevalence of informal taxation, which extends to all kinds of goods, even

those very slightly formally taxed (i.e. imports of manioc flour and maize from Togo), and to all types of

trade flows (imports, exports, re-exports, or transit). Moreover, the results of our econometric analysis

suggest a trade activity bias toward well-connected smugglers who are able to exchange goods with a high

unit value in large quantities. These smugglers seem to avoid paying formal taxes by paying informal ones.

Knowing that the average informal tax ratio is 1.6 percent and the average formal tax ratio that should be

applied is 6.5 percent, all the smugglers seem to be equal in the payments, both formal and informal, that

they end up making to the authorities.

20

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